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speecht5_sw_normal
Lingua-Connect/speecht5_sw_normal
speecht5_sw_normal is a text-to-audio model from Lingua-Connect. Use it for the text-to-audio task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text-to-Audio
- Library
- transformers
- License
- mit
- Model type
- speecht5
- Access
- Public
- Created
- Apr 2, 2025
- Updated
- Apr 3, 2025
- SHA
- 3dba351f
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
speecht5_sw_normal
This model is a fine-tuned version of microsoft/speecht5_tts on the arrow dataset. It achieves the following results on the evaluation set:
- Loss: 0.5708
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7131 | 2.003 | 500 | 0.6449 |
| 0.6108 | 4.006 | 1000 | 0.6056 |
| 0.6025 | 6.009 | 1500 | 0.5798 |
| 0.6159 | 8.012 | 2000 | 0.5708 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Apr 2, 2025
- Updated
- Apr 3, 2025